GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation

arXiv:2607.03869 · cs.CV, cs.AI · Submitted 2026-07-04 · Read on arXiv

cs.CV, cs.AI

Submitted: 2026-07-04

Updated: 2026-09-17

Comments: Accepted version. Published in IEEE Transactions on Geoscience and Remote Sensing, DOI: 10.1109/TGRS.2026.3734378. 22 pages

Journal ref: IEEE Transactions on Geoscience and Remote Sensing, 2026

DOI: 10.1109/TGRS.2026.3734378

Code: https://github.com/Avalon-S/GeoSelect

Project page: https://avalon-s.github.io/GeoSelect

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Benchmark — 24× in this paper · explained in 2 episodes
• Grounding — 11× in this paper · explained in 3 episodes
• Accuracy — 8× in this paper · explained in 1 episode
• Computer Vision and Pattern Recognition — 5× in this paper
• Ablation — 4× in this paper · explained in 1 episode
• Trace — 4× in this paper · explained in 2 episodes
• Transformer — 4× in this paper · explained in 2 episodes
• Visual Grounding — 4× in this paper · explained in 2 episodes
• Alignment — 3× in this paper · explained in 1 episode
• Decoupling — 3× in this paper · explained in 2 episodes
• Failure Modes — 3× in this paper · explained in 3 episodes
• Foundation Model — 3× in this paper · explained in 3 episodes
• Abstraction — 2× in this paper · explained in 1 episode
• Foundation Models — 2× in this paper · explained in 7 episodes
• Training-Free Framework — 2× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Decode — 1× in this paper · explained in 2 episodes
• Domain-Specific Language (DSL) — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• International Conference on Computer Vision — 1× in this paper
• International Conference on Learning Representations — 1× in this paper
• Robustness — 1× in this paper · explained in 5 episodes
• Scaffolding — 1× in this paper · explained in 3 episodes

Sources

• Cross-Modal Bidirectional Interaction Model for Referring Remote Sensing Image Segmentation
• Referring Remote Sensing Image Segmentation via Bidirectional Alignment Guided Joint Prediction
• SAM 3: Segment Anything with Concepts
• InstructSAM: A Training-Free Framework for Instruction-Oriented Remote Sensing Object Recognition
• SegEarth-R1: Geospatial Pixel Reasoning via Large Language Model
• GeoGround: A Unified Large Vision-Language Model for Remote Sensing Visual Grounding
• Enabling Training-Free Text-Based Remote Sensing Segmentation
• AUG: A New Dataset and An Efficient Model for Aerial Image Urban Scene Graph Generation
• RSGround-R1: Rethinking Remote Sensing Visual Grounding through Spatial Reasoning
• ProVG: Progressive Visual Grounding via Language Decoupling for Remote Sensing Imagery
• Qwen3 Technical Report
• Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs
• Falcon Mamba: The First Competitive Attention-free 7B Language Model
• The Llama 3 Herd of Models
• Generalized Referring Expression Segmentation on Aerial Photos

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